{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KyIvmcIeKIz8",
        "outputId": "8803b37c-fed4-47c9-da70-65603ad3fc7e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'TEXTurePaper'...\n",
            "remote: Enumerating objects: 91, done.\u001b[K\n",
            "remote: Counting objects: 100% (39/39), done.\u001b[K\n",
            "remote: Compressing objects: 100% (33/33), done.\u001b[K\n",
            "remote: Total 91 (delta 0), reused 39 (delta 0), pack-reused 52\u001b[K\n",
            "Unpacking objects: 100% (91/91), 103.02 MiB | 9.91 MiB/s, done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/TEXTurePaper/TEXTurePaper.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd TEXTurePaper"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4_JKehjbKn4Y",
        "outputId": "129d5f51-5747-4547-faeb-50a2452ecc0b"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/TEXTurePaper\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip uninstall -y torch torchvision torchtext"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z1thaIIGLWvM",
        "outputId": "9a744db1-edd8-4fe4-e828-63ca5c25f37d"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found existing installation: torch 1.13.1+cu116\n",
            "Uninstalling torch-1.13.1+cu116:\n",
            "  Successfully uninstalled torch-1.13.1+cu116\n",
            "Found existing installation: torchvision 0.14.1+cu116\n",
            "Uninstalling torchvision-0.14.1+cu116:\n",
            "  Successfully uninstalled torchvision-0.14.1+cu116\n",
            "Found existing installation: torchtext 0.14.1\n",
            "Uninstalling torchtext-0.14.1:\n",
            "  Successfully uninstalled torchtext-0.14.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SJAYDILLLqzm",
        "outputId": "8bba5677-0881-4a28-911a-fe2b509eb8c1"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/, https://download.pytorch.org/whl/cu113\n",
            "Collecting torch==1.12.1+cu113\n",
            "  Downloading https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp38-cp38-linux_x86_64.whl (1837.7 MB)\n",
            "\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m1.8/1.8 GB\u001b[0m \u001b[31m126.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0mtcmalloc: large alloc 1837744128 bytes == 0x2a80000 @  0x7f00d3ebc680 0x7f00d3edd824 0x5b3128 0x5bbc90 0x5f714c 0x64d800 0x527022 0x504866 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x5f5ee6 0x56bbe1 0x569d8a 0x5f60c3 0x56cc92 0x569d8a 0x5f60c3\n",
            "\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m1.8/1.8 GB\u001b[0m \u001b[31m120.0 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0mtcmalloc: large alloc 2297184256 bytes == 0x7031c000 @  0x7f00d3ebc680 0x7f00d3edcda2 0x5f714c 0x64d800 0x527022 0x504866 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x5f5ee6 0x56bbe1 0x569d8a 0x5f60c3 0x56cc92 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a\n",
            "tcmalloc: large alloc 1837744128 bytes == 0x2a80000 @  0x7f00d3ebc680 0x7f00d3edd824 0x5f97c1 0x5f8ecc 0x504866 0x56bbe1 0x569d8a 0x5f60c3 0x56bbe1 0x569d8a 0x5f60c3 0x50b32c 0x5f6b7b 0x66731d 0x5f6706 0x571143 0x50b22e 0x570b82 0x569d8a 0x50b3a0 0x570b82 0x569d8a 0x50b3a0 0x56cc92 0x501044 0x56be83 0x501044 0x56be83 0x501044 0x56be83 0x5f5ee6\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 GB\u001b[0m \u001b[31m929.3 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting torchvision==0.13.1+cu113\n",
            "  Downloading https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp38-cp38-linux_x86_64.whl (23.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m23.4/23.4 MB\u001b[0m \u001b[31m73.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting torchaudio==0.12.1\n",
            "  Downloading https://download.pytorch.org/whl/cu113/torchaudio-0.12.1%2Bcu113-cp38-cp38-linux_x86_64.whl (3.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.8/3.8 MB\u001b[0m \u001b[31m90.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch==1.12.1+cu113) (4.4.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from torchvision==0.13.1+cu113) (2.25.1)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.8/dist-packages (from torchvision==0.13.1+cu113) (7.1.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from torchvision==0.13.1+cu113) (1.21.6)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1+cu113) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1+cu113) (2022.12.7)\n",
            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1+cu113) (4.0.0)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1+cu113) (2.10)\n",
            "Installing collected packages: torch, torchvision, torchaudio\n",
            "  Attempting uninstall: torchaudio\n",
            "    Found existing installation: torchaudio 0.13.1+cu116\n",
            "    Uninstalling torchaudio-0.13.1+cu116:\n",
            "      Successfully uninstalled torchaudio-0.13.1+cu116\n",
            "Successfully installed torch-1.12.1+cu113 torchaudio-0.12.1+cu113 torchvision-0.13.1+cu113\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r requirements.txt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DjD_g6xkKrjh",
        "outputId": "207256dd-6439-41a3-9981-5a84501c8806"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: torch==1.12.1 in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 1)) (1.12.1+cu113)\n",
            "Requirement already satisfied: torchvision==0.13.1 in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 2)) (0.13.1+cu113)\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.26.0-py3-none-any.whl (6.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m89.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting diffusers\n",
            "  Downloading diffusers-0.12.1-py3-none-any.whl (604 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m604.0/604.0 KB\u001b[0m \u001b[31m36.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting accelerate\n",
            "  Downloading accelerate-0.16.0-py3-none-any.whl (199 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.7/199.7 KB\u001b[0m \u001b[31m23.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting huggingface-hub\n",
            "  Downloading huggingface_hub-0.12.0-py3-none-any.whl (190 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m22.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting ninja\n",
            "  Downloading ninja-1.11.1-py2.py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (145 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m146.0/146.0 KB\u001b[0m \u001b[31m18.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting xatlas\n",
            "  Downloading xatlas-0.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (229 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m229.2/229.2 KB\u001b[0m \u001b[31m23.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: imageio in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 9)) (2.9.0)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 10)) (3.2.2)\n",
            "Collecting pyrallis\n",
            "  Downloading pyrallis-0.3.1-py3-none-any.whl (33 kB)\n",
            "Collecting loguru\n",
            "  Downloading loguru-0.6.0-py3-none-any.whl (58 kB)\n",
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            "\u001b[?25hRequirement already satisfied: tqdm in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 13)) (4.64.1)\n",
            "Collecting einops\n",
            "  Downloading einops-0.6.0-py3-none-any.whl (41 kB)\n",
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            "\u001b[?25hRequirement already satisfied: opencv-python in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 15)) (4.6.0.66)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch==1.12.1->-r requirements.txt (line 1)) (4.4.0)\n",
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            "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from torchvision==0.13.1->-r requirements.txt (line 2)) (2.25.1)\n",
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            "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers->-r requirements.txt (line 3)) (3.9.0)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers->-r requirements.txt (line 3)) (2022.6.2)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers->-r requirements.txt (line 3)) (23.0)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
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            "\u001b[?25hRequirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers->-r requirements.txt (line 3)) (6.0)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.8/dist-packages (from diffusers->-r requirements.txt (line 4)) (6.0.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.8/dist-packages (from accelerate->-r requirements.txt (line 5)) (5.4.8)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib->-r requirements.txt (line 10)) (3.0.9)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.8/dist-packages (from matplotlib->-r requirements.txt (line 10)) (0.11.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib->-r requirements.txt (line 10)) (1.4.4)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib->-r requirements.txt (line 10)) (2.8.2)\n",
            "Collecting typing-inspect\n",
            "  Downloading typing_inspect-0.8.0-py3-none-any.whl (8.7 kB)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.1->matplotlib->-r requirements.txt (line 10)) (1.15.0)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.8/dist-packages (from importlib-metadata->diffusers->-r requirements.txt (line 4)) (3.12.0)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1->-r requirements.txt (line 2)) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1->-r requirements.txt (line 2)) (2.10)\n",
            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1->-r requirements.txt (line 2)) (4.0.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->torchvision==0.13.1->-r requirements.txt (line 2)) (2022.12.7)\n",
            "Collecting mypy-extensions>=0.3.0\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Installing collected packages: xatlas, tokenizers, ninja, mypy-extensions, loguru, einops, typing-inspect, huggingface-hub, accelerate, transformers, pyrallis, diffusers\n",
            "Successfully installed accelerate-0.16.0 diffusers-0.12.1 einops-0.6.0 huggingface-hub-0.12.0 loguru-0.6.0 mypy-extensions-1.0.0 ninja-1.11.1 pyrallis-0.3.1 tokenizers-0.13.2 transformers-4.26.0 typing-inspect-0.8.0 xatlas-0.0.7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install kaolin==0.12.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-1.12.1_cu113.html"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eb_GTMy3OVmy",
        "outputId": "8e2f8289-96a8-4ae6-9f86-26bb92fb9c4a"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Looking in links: https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-1.12.1_cu113.html\n",
            "Collecting kaolin==0.12.0\n",
            "  Downloading https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-1.12.1_cu113/kaolin-0.12.0-cp38-cp38-manylinux1_x86_64.whl (9.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.8/9.8 MB\u001b[0m \u001b[31m4.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting tornado==6.1\n",
            "  Downloading tornado-6.1-cp38-cp38-manylinux2010_x86_64.whl (427 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m427.5/427.5 KB\u001b[0m \u001b[31m25.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting Pillow>=8.0.0\n",
            "  Downloading Pillow-9.4.0-cp38-cp38-manylinux_2_28_x86_64.whl (3.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m93.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting usd-core<22.8\n",
            "  Downloading usd_core-22.5.post1-cp38-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (24.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.3/24.3 MB\u001b[0m \u001b[31m38.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting scipy<=1.7.2,>=1.2.0\n",
            "  Downloading scipy-1.7.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m39.3/39.3 MB\u001b[0m \u001b[31m15.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting flask==2.0.3\n",
            "  Downloading Flask-2.0.3-py3-none-any.whl (95 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m95.6/95.6 KB\u001b[0m \u001b[31m11.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.51.0 in /usr/local/lib/python3.8/dist-packages (from kaolin==0.12.0) (4.64.1)\n",
            "Collecting Jinja2>=3.0\n",
            "  Downloading Jinja2-3.1.2-py3-none-any.whl (133 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m133.1/133.1 KB\u001b[0m \u001b[31m16.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: click>=7.1.2 in /usr/local/lib/python3.8/dist-packages (from flask==2.0.3->kaolin==0.12.0) (7.1.2)\n",
            "Collecting Werkzeug>=2.0\n",
            "  Downloading Werkzeug-2.2.2-py3-none-any.whl (232 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m232.7/232.7 KB\u001b[0m \u001b[31m26.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting itsdangerous>=2.0\n",
            "  Downloading itsdangerous-2.1.2-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: numpy<1.23.0,>=1.16.5 in /usr/local/lib/python3.8/dist-packages (from scipy<=1.7.2,>=1.2.0->kaolin==0.12.0) (1.21.6)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.8/dist-packages (from Jinja2>=3.0->flask==2.0.3->kaolin==0.12.0) (2.0.1)\n",
            "Collecting MarkupSafe>=2.0\n",
            "  Downloading MarkupSafe-2.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25 kB)\n",
            "Installing collected packages: usd-core, tornado, scipy, Pillow, MarkupSafe, itsdangerous, Werkzeug, Jinja2, flask, kaolin\n",
            "  Attempting uninstall: tornado\n",
            "    Found existing installation: tornado 6.0.4\n",
            "    Uninstalling tornado-6.0.4:\n",
            "      Successfully uninstalled tornado-6.0.4\n",
            "  Attempting uninstall: scipy\n",
            "    Found existing installation: scipy 1.7.3\n",
            "    Uninstalling scipy-1.7.3:\n",
            "      Successfully uninstalled scipy-1.7.3\n",
            "  Attempting uninstall: Pillow\n",
            "    Found existing installation: Pillow 7.1.2\n",
            "    Uninstalling Pillow-7.1.2:\n",
            "      Successfully uninstalled Pillow-7.1.2\n",
            "  Attempting uninstall: MarkupSafe\n",
            "    Found existing installation: MarkupSafe 2.0.1\n",
            "    Uninstalling MarkupSafe-2.0.1:\n",
            "      Successfully uninstalled MarkupSafe-2.0.1\n",
            "  Attempting uninstall: itsdangerous\n",
            "    Found existing installation: itsdangerous 1.1.0\n",
            "    Uninstalling itsdangerous-1.1.0:\n",
            "      Successfully uninstalled itsdangerous-1.1.0\n",
            "  Attempting uninstall: Werkzeug\n",
            "    Found existing installation: Werkzeug 1.0.1\n",
            "    Uninstalling Werkzeug-1.0.1:\n",
            "      Successfully uninstalled Werkzeug-1.0.1\n",
            "  Attempting uninstall: Jinja2\n",
            "    Found existing installation: Jinja2 2.11.3\n",
            "    Uninstalling Jinja2-2.11.3:\n",
            "      Successfully uninstalled Jinja2-2.11.3\n",
            "  Attempting uninstall: flask\n",
            "    Found existing installation: Flask 1.1.4\n",
            "    Uninstalling Flask-1.1.4:\n",
            "      Successfully uninstalled Flask-1.1.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "notebook 5.7.16 requires jinja2<=3.0.0, but you have jinja2 3.1.2 which is incompatible.\n",
            "google-colab 1.0.0 requires tornado~=6.0.4, but you have tornado 6.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed Jinja2-3.1.2 MarkupSafe-2.1.2 Pillow-9.4.0 Werkzeug-2.2.2 flask-2.0.3 itsdangerous-2.1.2 kaolin-0.12.0 scipy-1.7.2 tornado-6.1 usd-core-22.5.post1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install imageio-ffmpeg"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UmtR6VznTddy",
        "outputId": "666f2c7e-b425-4203-adcd-7a1a269c75b9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting imageio-ffmpeg\n",
            "  Downloading imageio_ffmpeg-0.4.8-py3-none-manylinux2010_x86_64.whl (26.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m26.9/26.9 MB\u001b[0m \u001b[31m16.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: imageio-ffmpeg\n",
            "Successfully installed imageio-ffmpeg-0.4.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!huggingface-cli login"
      ],
      "metadata": {
        "id": "FtjDWT8TNo0o"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!python -m scripts.run_texture --config_path=configs/text_guided/nascar.yaml"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FR7uyVVOOAUD",
        "outputId": "b80781c4-5e73-46e6-ff92-4d9a722e3ef1"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[32m2023-02-06 15:27:03\u001b[0m \u001b[1mrunning xatlas to unwrap UVs for mesh: v={v_np.shape} f={f_np.shape}\u001b[0m\n",
            "\u001b[32m2023-02-06 15:27:06\u001b[0m \u001b[1mLoaded Mesh, #parameters: 6337536\u001b[0m\n",
            "\u001b[32m2023-02-06 15:27:06\u001b[0m \u001b[1mTexturedMeshModel()\u001b[0m\n",
            "\u001b[32m2023-02-06 15:27:06\u001b[0m \u001b[33m\u001b[1mtry to load hugging face access token from the default place, make sure you have run `huggingface-cli login`.\u001b[0m\n",
            "\u001b[32m2023-02-06 15:27:06\u001b[0m \u001b[1mloading stable diffusion with stabilityai/stable-diffusion-2-depth...\u001b[0m\n",
            "Downloading (…)_pytorch_model.bin\";: 100% 335M/335M [00:05<00:00, 61.7MB/s]\n",
            "Downloading (…)main/vae/config.json: 100% 716/716 [00:00<00:00, 301kB/s]\n",
            "Downloading (…)tokenizer/vocab.json: 100% 1.06M/1.06M [00:01<00:00, 800kB/s]\n",
            "Downloading (…)tokenizer/merges.txt: 100% 525k/525k [00:01<00:00, 474kB/s]\n",
            "Downloading (…)cial_tokens_map.json: 100% 460/460 [00:00<00:00, 180kB/s]\n",
            "Downloading (…)okenizer_config.json: 100% 923/923 [00:00<00:00, 383kB/s]\n",
            "Downloading (…)_encoder/config.json: 100% 732/732 [00:00<00:00, 288kB/s]\n",
            "Downloading (…)\"pytorch_model.bin\";: 100% 1.36G/1.36G [00:12<00:00, 111MB/s]\n",
            "Downloading (…)_pytorch_model.bin\";: 100% 3.46G/3.46G [00:52<00:00, 66.3MB/s]\n",
            "Downloading (…)ain/unet/config.json: 100% 1.07k/1.07k [00:00<00:00, 358kB/s]\n",
            "Downloading (…)_pytorch_model.bin\";: 100% 3.46G/3.46G [00:54<00:00, 63.7MB/s]\n",
            "Downloading (…)ain/unet/config.json: 100% 914/914 [00:00<00:00, 367kB/s]\n",
            "\u001b[32m2023-02-06 15:30:09\u001b[0m \u001b[1m\t successfully loaded stable diffusion!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:09\u001b[0m \u001b[1mA next gen nascar, front view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:09\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:09\u001b[0m \u001b[1m['A next gen nascar, front view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:09\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267,  2184,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mA next gen nascar, left view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1m['A next gen nascar, left view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267,  1823,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mA next gen nascar, back view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1m['A next gen nascar, back view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267,   893,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mA next gen nascar, right view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1m['A next gen nascar, right view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267,  1155,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mA next gen nascar, overhead view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1m['A next gen nascar, overhead view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267, 20321,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mA next gen nascar, bottom view\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mNone\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1m['A next gen nascar, bottom view']\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:12\u001b[0m \u001b[1mtensor([[49406,   320,  1131,  3278,  7868,   267,  5931,  1093, 49407,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0,     0,     0,     0,\n",
            "             0,     0,     0,     0,     0,     0,     0]])\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:13\u001b[0m \u001b[1mphis: [0.0, 45.0, 315.0, 90.0, 270.0, 135.0, 225.0, 180.0]\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:13\u001b[0m \u001b[1mSuccessfully initialized nascar\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:13\u001b[0m \u001b[1mStarting training ^_^\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:13\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #0...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:14\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:14\u001b[0m \u001b[1m--- Painting step #1 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:14\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 0.0, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:15\u001b[0m \u001b[1mtext: A next gen nascar, front view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:30:36\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #1...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:38\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:38\u001b[0m \u001b[1m--- Painting step #2 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:38\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 0.7853981852531433, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:38\u001b[0m \u001b[1mtext: A next gen nascar, left view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:30:57\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #2...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:58\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:58\u001b[0m \u001b[1m--- Painting step #3 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:58\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 5.497786998748779, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:30:58\u001b[0m \u001b[1mtext: A next gen nascar, right view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:31:17\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #3...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:18\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:18\u001b[0m \u001b[1m--- Painting step #4 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:18\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 1.5707963705062866, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:19\u001b[0m \u001b[1mtext: A next gen nascar, left view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:31:38\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #4...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:39\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:39\u001b[0m \u001b[1m--- Painting step #5 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:39\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 4.71238899230957, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:31:40\u001b[0m \u001b[1mtext: A next gen nascar, right view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:31:59\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #5...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:01\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:01\u001b[0m \u001b[1m--- Painting step #6 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:01\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 2.356194496154785, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:01\u001b[0m \u001b[1mtext: A next gen nascar, left view\u001b[0m\n",
            " 60% 6/10 [01:46<01:17, 19.43s/it]\n",
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            "\u001b[32m2023-02-06 15:32:20\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #6...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:21\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:21\u001b[0m \u001b[1m--- Painting step #7 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:21\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 3.9269907474517822, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:21\u001b[0m \u001b[1mtext: A next gen nascar, right view\u001b[0m\n",
            " 70% 7/10 [02:07<00:59, 19.74s/it]\n",
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            "\u001b[32m2023-02-06 15:32:40\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #7...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:41\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:41\u001b[0m \u001b[1m--- Painting step #8 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:41\u001b[0m \u001b[1mPainting from theta: 1.0471975803375244, phi: 3.1415927410125732, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:32:42\u001b[0m \u001b[1mtext: A next gen nascar, back view\u001b[0m\n",
            " 80% 8/10 [02:27<00:39, 19.95s/it]\n",
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            "\u001b[32m2023-02-06 15:33:01\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #8...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:03\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:03\u001b[0m \u001b[1m--- Painting step #9 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:03\u001b[0m \u001b[1mPainting from theta: 0.5235987901687622, phi: 3.1415927410125732, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:03\u001b[0m \u001b[1mtext: A next gen nascar, overhead view\u001b[0m\n",
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            "\u001b[32m2023-02-06 15:33:22\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #9...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:24\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:24\u001b[0m \u001b[1m--- Painting step #10 ---\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:24\u001b[0m \u001b[1mPainting from theta: 2.6179938316345215, phi: 3.1415927410125732, radius: 1.5\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:24\u001b[0m \u001b[1mtext: A next gen nascar, bottom view\u001b[0m\n",
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            "fitting mesh colors:  95% 190/200 [00:04<00:00, 41.60it/s]\u001b[A\n",
            "fitting mesh colors:  98% 195/200 [00:04<00:00, 41.70it/s]\u001b[A\n",
            "fitting mesh colors: 100% 200/200 [00:04<00:00, 41.75it/s]\n",
            "\u001b[32m2023-02-06 15:33:43\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #10...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:44\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:44\u001b[0m \u001b[1mFinished Painting ^_^\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:44\u001b[0m \u001b[1mSaving the last result...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:44\u001b[0m \u001b[1mEvaluating and saving model, painting iteration #10...\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mSaving mesh to experiments/nascar/mesh\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mwriting obj mesh to {obj_file}\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mwriting vertices {v_np.shape}\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mwriting vertices texture coords {vt_np.shape}\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1mwriting faces {f_np.shape}\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1m\tDone!\u001b[0m\n",
            "\u001b[32m2023-02-06 15:33:59\u001b[0m \u001b[1m\tDone!\u001b[0m\n",
            "100% 10/10 [03:45<00:00, 22.50s/it]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls -al /content/TEXTurePaper/experiments/nascar/results"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "olr4XckiYHxb",
        "outputId": "fd9ee9cf-2f81-4daf-f98b-5fb51809f2ea"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 4212\n",
            "drwxr-xr-x 2 root root    4096 Feb  6 15:33 .\n",
            "drwxr-xr-x 6 root root    4096 Feb  6 15:33 ..\n",
            "-rw-r--r-- 1 root root 2983647 Feb  6 15:33 step_00010_rgb.mp4\n",
            "-rw-r--r-- 1 root root 1316551 Feb  6 15:33 step_00010_texture.png\n"
          ]
        }
      ]
    }
  ]
}